CN102638566A - BLOG system running method based on cloud storage - Google Patents
BLOG system running method based on cloud storage Download PDFInfo
- Publication number
- CN102638566A CN102638566A CN2012100489343A CN201210048934A CN102638566A CN 102638566 A CN102638566 A CN 102638566A CN 2012100489343 A CN2012100489343 A CN 2012100489343A CN 201210048934 A CN201210048934 A CN 201210048934A CN 102638566 A CN102638566 A CN 102638566A
- Authority
- CN
- China
- Prior art keywords
- client
- hadoop
- request
- user
- node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Abstract
The invention discloses a BLOG system running method based on cloud storage, and belongs to the technical field of cloud computing. The BLOG system running method is mainly implemented by a blog system and a cloud storage system, wherein the cloud storage system consists of a distributed file system and a virtualized server cluster; the distributed file system adopts an HADOOP and comprises Hadoop distributed file system (HDFS) architecture at bottom layer, a MapReduce algorithm at the upper layer, and a client; the HADOOP receives a request from the client; a NameNode of the HDFS responds to the request and distributes specific operation tasks onto subordinate DateNode; and according to MapReduce function calculation, a final result is obtained and returned to the client. According to the BLOG system running method, the technical problems that a server wastes resources, is low in storage efficiency, is low in system running speed and the like during storage of the blog system are solved, and the problems of the scalability of a storage space of the server and the safety and the stability of storage resources in the server are solved.
Description
Technical field
The present invention relates to a kind of BLOG system operation method, belong to the cloud computing technical field based on the cloud storage.
Background technology
Along with development of times, this network application technology of blog has got into huge numbers of families.Complicated day by day along with blog system, and the increase gradually of using the user, the traditional centralized storage means has been difficult to satisfy the demand of its development, and the architectural of file storage changes the trend that also just becomes a kind of epoch.How can carry out timely, effective, safe storage and management, how can realize on limited volume hardware resource when guaranteeing server stability that the maximization of storage just becomes the critical problem that present each large enterprises need solve data such as the daily record of blog user, people's archives.The appearance of the Intel Virtualization Technology of cloth formula file storage and server then exactly can solve above-mentioned variety of problems.
The storage of traditional blog system generally all is to concentrate to share the formula storage; Promptly; All resources store on the same station server with a kind of mode of writing direct, and have caused the waste of hardware resource, and can not guarantee the fail safe and the reliability of blog system data resource.This storage mode all has totally unfavorable influence to the backup capabilities of data in the transmission speed of the arithmetic speed of blog system, data and the server equally, and has strengthened the cost of the operation and management of enterprise.
The present invention can realize the storage to blog system data resource low-cost high-efficiency high security through the use of cloud memory technology, with traditional blog system storage system structural difference is arranged.The cloud memory technology can be deployed to the memory space of blog system on the hardware storage device of a large amount of different model different scales, and carries out unified management and configuration.Through the collaborative work that the large server cluster in the cloud storage architecture, distributed file system etc. are joined together, the interface or the software of stores service and access services is provided to the user.The use of cloud memory technology has improved the storage efficiency of blog system, the extensibility of memory space and the fail safe of storage data resource greatly.Like the patent No. is 200620167567.9; Name is called " based on the distributed E-mail system of Virtual Private Network and distributed storage mode "; Though adopted the algorithm of distributed document storage; But but do not realize the virtual of server, so load balancing that still can't the settlement server cluster, the functions such as automated back-up of data resource.
The memory data output of blog system generally all is very huge; Traditional storage mode has been difficult to satisfy the storage of so huge data again; Yet the cloud memory technology but can be carried out distributed arithmetic to this large batch of data, has realized the efficient storage of data and has guaranteed the fail safe of data resource in the server stores space.
Summary of the invention
To the deficiency of traditional blog system memory technology, the present invention proposes a kind of BLOG (blog) system operation method based on the cloud storage.
Technical scheme of the present invention is following:
A kind of BLOG (blog) system operation method based on the cloud storage; Mainly realize by following system; This system comprises blog system and cloud storage system, and cloud storage system mainly is made up of distributed file system and virtualized server cluster, and wherein distributed file system adopts HADOOP; The virtualized server cluster has adopted VMWare WorkStation enterprise virtualization software; The HADOOP system comprises that mainly bottom HDFS framework, upper strata MapReduce algorithm and Client client HADOOP system receive the request from the Client client, through NameNode node (control module of the distributed file system) response request of HDFS (the distributed file system module of HADOOP), and the concrete operations Task Distribution to its subordinate's DateNode node (memory module of distributed file system); Computing through MapReduce function on the DataNode node; Obtain final result, and turn back to the result on the Client, this operation method step is following:
A. at server end VMWare WorkStation is installed, accomplishes the establishment of a plurality of virtual machines and the installation of (SuSE) Linux OS, and realize building of cluster virtual machine;
B. HADOOP is deployed on this server cluster, selects a virtual machine as Client, one as the NameNode node, and remaining is as the DataNode node, and on each node, configures the MapReduce function;
C. at the Client of HADOOP deploy LAMP (Linux+Apache+MySQL+PHP) framework, and among the Apache and MySQL that the source file and the database file of blog system is put into LAMP respectively, change steps d, step e and step f respectively over to;
D. the user lands blog system; Upload file; HADOOP receives user's request through Client, and carries out the operation that writes file, is deployed to file on subordinate's the DataNode node through NameNode node dispenser; Distributed storage through MapReduce function realization file changes step g over to;
E. user's download article picture, HADOOP carries out read operation through the request that Client receives the user; Management through the NameNode node; Reading of data resource from the DataNode node, and realize the integration of data through the MapReduce function, and will integrate good data and output to Client and hold; Send the user to, change step g over to;
F. the user checks the blog data, and HADOOP carries out and checks operation through the request that Client receives the user; Control through the NameNode node; Obtain the particular location of file storage from the DataNode node, integrate, and final data is returned to the Client end through the MapReduce function; Realize user's look facility, change step g over to;
G. accomplish the read-write capability of HADOOP system, server resource is reintegrated, and Client detects the variation of HADOOP, and carries out the renewal of user interface.
HADOOP receives user's request through Client in the steps d of above-mentioned operation method, and carries out the operation that writes file, and step is following:
< 1>user adds file to blog system, and Client receives the request that writes from the user;
< 2>Client sends the request that writes to HADOOP, and the NameNode node among the HADOOP receives request, and is used for receiving through the call function new file that to create a state be under construction (creating) and writes file, and sends response;
< 3>Client receives the response from the Namenode node, and the data block that file is divided into one by one writes in the DataNode node, and in ablation process, realizes the backup of data;
< 4>data write completion, send into function signal and give client;
< 5>client receives into function signal, and the signal that successfully writes data is sent to the user, and whole data write operation is accomplished.
HADOOP receives user's request through Client among the step e of above-mentioned operation method, carries out read operation, and step is following:
1>Client receives user's the request of reading, and through call function HADOOP is mail in request;
2>the NameNode node of HADOOP (control module of distributed file system) receives the request from Client, from its locatedBlocks, searches resource location, and creates and read in stream, sends data read command to the DataNode node;
3>the DataNode node receives the reading order from the NameNode node, sets up client link monitoring through function call, sends to client after the local data on the DataNode node is integrated;
4>the HADOOP data read completion, send to Client and read the completion signal;
5>Client receive from HADOOP read the completion signal, accomplish user's reading of data request.
HADOOP receives user's request through Client among the step f of above-mentioned operation method, carries out and checks operation, and step is following:
< a>user sends the request open file to Client, and Client receives request, and asks to the HADOOP transmission through calling DistributedFileSystem.open (Path f, int bufferSize) the function function of path (be used to open file);
The NameNode node of <b>HADOOP receives the request from Client, calls through RPC, obtains the data storage location chained list, forms DFSInputStream (inlet flow that comprises data resource position in DataNode) object, and response is sent to Client;
< c>Client receives response, accomplishes the packing of FSDataInputStream (class of using when directly checking the HDFS system data is used such form reading of data from HDFS with stream), returns to the user;
< d>user receives FSDataInputStream, and the opening operation of file is accomplished.
Above-mentioned HADOOP is a distributed file system architecture.
The English original meaning of above-mentioned Client is client, client, trustee etc., means client here.
Above-mentioned WordPress is a kind of blog platform of the PHP of use language development, and the user can set up the net annal of oneself on the server of supporting PHP and MySQL database.Also can be used as a Content Management System (CMS) to WordPress uses.WordPress is a free project of increasing income, and under gnu general public license, authorizes issue.
Above-mentioned HDFS is the system module of distributed file system HADOOP.
Above-mentioned DFSInputStream to as if comprise the inlet flow of data resource position in DataNode.
The above-mentioned under construction meaning is to create.
Above-mentioned NameNode is the control module of distributed file system.
Above-mentioned DataNode is the memory module of distributed file system.
Employed blog system is wordpress on cloud storage system of the present invention, and wordpress increases income in the blog system with one of product the most widely at present.This blog system is based on that PHP+MyAQL builds, and has very strong functions property application, supports various plug-in units, and source code very simply is beneficial to keeper's the work that administers and maintains.
Distributed file system can store data resource on many dissimilar memory devices into and carries out unified management; Its extensibility is fabulous, and can effectively alleviate the load of server, the storage efficiency that improves server and the speed of service of system through the distributed arithmetic between many service memory equipment.HADOOP has better fault-tolerant ability than other distributed file systems, and its requirement for the storage hardware resource is lower, can be deployed on any cheap hardware.
Intel Virtualization Technology can fictionalize many virtual machines to a server; And these virtual machines are linked together; Form large-scale server cluster; Through various configurations and deployment, make its base layer support framework that becomes distributed file system, the distributed document storage of building on based on virtualized server cluster to server cluster; Can realize the load balancing of cluster, the dynamic migration of data, the work such as automated back-up of data easily, make the more convenient of file storage change and guaranteed the fail safe of storing.VMWare WorkStation is present the most general server virtualization software, and the convenience of its use is easy to the property learnt, and it is the reason that the present invention selects it that the agility of disposing is installed.
The invention solves that the server resource waste, the storage efficiency that run in the blog system storage are low, system running speed waits technical matters slowly, and solve the problem of fail safe and stability of the scalability in server stores space, server memory storage resource.
Description of drawings
Fig. 1 is the structural representation of system of the present invention.
Wherein: 1, blog system, 2, network interface, 3, the HADOOP system, 4, the virtualized server cluster.
Fig. 2 is HDFS (distributed file system) structural representation of HADOOP system in the system of the present invention.
Wherein: 5, Client (client), 6, NameNode (control module of distributed file system), 7, DataNode (memory module of distributed file system).
Fig. 3 is the FB(flow block) of system operation method of the present invention, and wherein a～g is each step wherein.
Fig. 4 is that the HADOOP in the system operation method steps d of the present invention receives user's request through Client, and carries out the FB(flow block) of the operation that writes file, and wherein < 1 >～< 5>are each step wherein.
Fig. 5 is that the HADOOP among the system operation method step e of the present invention receives user's request through Client, and carries out the FB(flow block) of the operation of reading file, wherein 1 >～5>is each step wherein.
Fig. 6 is that the HADOOP among the system operation method step f of the present invention receives user's request through Client, and carries out the FB(flow block) of the operation of viewing files, and wherein < a >～< d>is each step wherein.
Embodiment
Below in conjunction with accompanying drawing and embodiment the present invention is further specified, but be not limited thereto.
Embodiment:
The embodiment of the invention is shown in Fig. 1-3; A kind of BLOG (blog) system operation method based on the cloud storage; Realized by following system that mainly this system comprises blog system 1 and cloud storage system, cloud storage system mainly is made up of distributed file system and virtualized server cluster 4; Wherein distributed file system adopts HADOOP; Virtualized server cluster 4 has adopted VMWare WorkStation enterprise virtualization software, and HADOOP system 3 mainly comprises bottom HDFS framework, upper strata MapReduce algorithm and Client client 5, the request that HADOOP system 3 receives from Client client 5; NameNode6 node (control module of distributed file system) response request through HDFS (the distributed file system module of HADOOP); And the concrete operations Task Distribution to its subordinate's the DateNode7 node (memory module of distributed file system), the computing through MapReduce function on the DataNode7 node obtains final result; And turn back to the result on the Client5, this operation method step is following:
A. at server end VMWare WorkStation is installed, accomplishes the establishment of a plurality of virtual machines and the installation of (SuSE) Linux OS, and realize building of cluster virtual machine;
B. HADOOP is deployed on this server cluster, selects a virtual machine as Client, one as the NameNode node, and remaining is as the DataNode node, and on each node, configures the MapReduce function;
C. at the Client of HADOOP deploy LAMP (Linux+Apache+MySQL+PHP) framework, and among the Apache and MySQL that the source file and the database file of blog system is put into LAMP respectively, change steps d, step e and step f respectively over to;
D. the user lands blog system; Upload file; HADOOP receives user's request through Client, and carries out the operation that writes file, is deployed to file on subordinate's the DataNode node through NameNode node dispenser; Distributed storage through MapReduce function realization file changes step g over to;
E. user's download article picture, HADOOP carries out read operation through the request that Client receives the user; Management through the NameNode node; Reading of data resource from the DataNode node, and realize the integration of data through the MapReduce function, and will integrate good data and output to Client and hold; Send the user to, change step g over to;
F. the user checks the blog data, and HADOOP carries out and checks operation through the request that Client receives the user; Control through the NameNode node; Obtain the particular location of file storage from the DataNode node, integrate, and final data is returned to the Client end through the MapReduce function; Realize user's look facility, change step g over to;
G. accomplish the read-write capability of HADOOP system, server resource is reintegrated, and Client detects the variation of HADOOP, and carries out the renewal of user interface.
HADOOP receives user's request through Client in the steps d of above-mentioned operation method, and carries out the operation that writes file, and as shown in Figure 4, step is following:
< 1>user adds file to blog system, and Client receives the request that writes from the user;
< 2>Cl ient sends the request that writes to HADOOP, and the NameNode node among the HADOOP receives request, and is used for receiving through the call function new file that to create a state be under construction (creating) and writes file, and sends response;
< 3>Client receives the response from the Namenode node, and the data block that file is divided into one by one writes in the DataNode node, and in ablation process, realizes the backup of data;
< 4>data write completion, send into function signal and give client;
< 5>client receives into function signal, and the signal that successfully writes data is sent to the user, and whole data write operation is accomplished.
HADOOP receives user's request through Client among the step e of above-mentioned operation method, carries out read operation, and as shown in Figure 5, step is following:
1>Client receives user's the request of reading, and through call function HADOOP is mail in request;
2>the NameNode node of HADOOP (control module of distributed file system) receives the request from Client, from its locatedBlocks, searches resource location, and creates and read in stream, sends data read command to the DataNode node;
3>the DataNode node receives the reading order from the NameNode node, sets up client link monitoring through function call, sends to client after the local data on the DataNode node is integrated;
4>the HADOOP data read completion, send to Client and read the completion signal;
5>Client receive from HADOOP read the completion signal, accomplish user's reading of data request.
HADOOP receives user's request through Client among the step f of above-mentioned operation method, carries out and checks operation, and as shown in Figure 6, step is following:
< a>user sends the request open file to Client, and Client receives request, and asks to the HADOOP transmission through calling DistributedFileSystem.open (Path f, int bufferSize) the function function of path (be used to open file);
The NameNode node of <b>HADOOP receives the request from Client, calls through RPC, obtains the data storage location chained list, forms DFSInputStream (inlet flow that comprises data resource position in DataNode) object, and response is sent to Client;
< c>Client receives response, accomplishes the packing of FSDataInputStream (class of using when directly checking the HDFS system data is used such form reading of data from HDFS with stream), returns to the user;
< d>user receives FSDataInputStream, and the opening operation of file is accomplished.
Claims (4)
1. BLOG system operation method based on cloud storage; Realized by following system that mainly this system comprises blog system and cloud storage system, cloud storage system mainly is made up of distributed file system and virtualized server cluster; Wherein distributed file system adopts HADOOP; The virtualized server cluster has adopted VMWare WorkStation enterprise virtualization software, and the HADOOP system mainly comprises bottom HDFS framework, upper strata MapReduce algorithm and Client client, and the HADOOP system receives the request from the Client client; NameNode node response request through HDFS; And the concrete operations Task Distribution to its subordinate's DateNode node, the computing through MapReduce function on the DataNode node obtains final result; And turn back to the result on the Client client, this operation method step is following:
A. at server end VMWare WorkStation is installed, accomplishes the establishment of a plurality of virtual machines and the installation of (SuSE) Linux OS, and realize building of cluster virtual machine;
B. HADOOP is deployed on this server cluster, selects a virtual machine as Client, one as the NameNode node, and remaining is as the DataNode node, and on each node, configures the MapReduce function;
C. at the Client of HADOOP deploy LAMP framework, and among the Apache and MySQL that the source file and the database file of blog system is put into LAMP respectively, change steps d, step e and step f respectively over to;
D. the user lands blog system; Upload file; HADOOP receives user's request through Client; And carry out the operation write file file is deployed to through NameNode node dispenser on subordinate's the DataNode node, realize the distributed storage of file changing step g over to through the MapReduce function;
E. user's download article picture, HADOOP carries out read operation through the request that Client receives the user; Management through the NameNode node; Reading of data resource from the DataNode node, and realize the integration of data through the MapReduce function, and will integrate good data and output to Client and hold; Send the user to, change step g over to;
F. the user checks the blog data, and HADOOP carries out and checks operation through the request that Client receives the user; Control through the NameNode node; Obtain the particular location of file storage from the DataNode node, integrate, and final data is returned to the Client end through the MapReduce function; Realize user's look facility, change step g over to;
G. accomplish the read-write capability of HADOOP system, server resource is reintegrated, and Client detects the variation of HADOOP, and carries out the renewal of user interface.
One kind according to claim 1 in the steps d of operation method HADOOP receive user's request through Client,
And carry out the operation that writes file, step is following:
< 1>user adds file to blog system, and Client receives the request that writes from the user;
< 2>Client sends the request that writes to HADOOP, and the NameNode node among the HADOOP receives request, and is used for receiving through the call function new file that to create a state be under construction and writes file, and sends response;
< 3>Client receives the response from the Namenode node, and the data block that file is divided into one by one writes in the DataNode node, and in ablation process, realizes the backup of data;
< 4>data write completion, send into function signal and give client;
< 5>client receives into function signal and the signal that successfully writes data is sent to the user, and whole data write operation is accomplished.
One kind according to claim 1 among the step e of operation method HADOOP receive user's request through Client, carry out read operation, step is following:
1>Client receives user's the request of reading, and through call function HADOOP is mail in request;
2>the NameNode node of HADOOP receives the request from Client, from its locatedBlocks, searches resource location, and creates and read in stream, sends data read command to the DataNode node;
3>the DataNode node receives the reading order from the NameNode node, sets up client link monitoring through function call, sends to client after the local data on the DataNode node is integrated;
4>the HADOOP data read completion, send to Client and read the completion signal;
5>Client receive from HADOOP read the completion signal, accomplish user's reading of data request.
One kind according to claim 1 among the step f of operation method HADOOP receive user's request through Client, carry out and check operation, step is following:
< a>user is to the request of Client transmission viewing files, and Client receives request, and sends request through calling the DistributedFileSystem.open function to HADOOP;
The NameNode node of <b>HADOOP receives the request from Client, calls through RPC, obtains the data storage location chained list, forms the DFSInputStream object, and response is sent to Client;
< c>Client receives response, accomplishes the packing of FSDataInputStream, returns to the user;
< d>user receives FSDataInputStream, and the operation of checking of file is accomplished.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210048934.3A CN102638566B (en) | 2012-02-28 | 2012-02-28 | BLOG system running method based on cloud storage |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210048934.3A CN102638566B (en) | 2012-02-28 | 2012-02-28 | BLOG system running method based on cloud storage |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102638566A true CN102638566A (en) | 2012-08-15 |
| CN102638566B CN102638566B (en) | 2015-03-04 |
Family
ID=46622807
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210048934.3A Expired - Fee Related CN102638566B (en) | 2012-02-28 | 2012-02-28 | BLOG system running method based on cloud storage |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102638566B (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102882927A (en) * | 2012-08-29 | 2013-01-16 | 华南理工大学 | Cloud storage data synchronizing framework and implementing method thereof |
| CN102880531A (en) * | 2012-09-27 | 2013-01-16 | 新浪网技术(中国)有限公司 | Database backup system and backup method and slave database server of database backup system |
| CN103023995A (en) * | 2012-11-29 | 2013-04-03 | 中国电力科学研究院 | Hadoop-based distributive type cloud storage type automatic grading data managing system |
| CN103024020A (en) * | 2012-12-05 | 2013-04-03 | 蓝盾信息安全技术股份有限公司 | Network data file storing method and device based on WEB application |
| CN103124299A (en) * | 2013-03-21 | 2013-05-29 | 杭州电子科技大学 | Distributed block-level storage system in heterogeneous environment |
| CN103428292A (en) * | 2013-08-20 | 2013-12-04 | 浪潮集团有限公司 | Device and method for effectively storing big data |
| CN103853612A (en) * | 2012-12-04 | 2014-06-11 | 中山大学深圳研究院 | Method for reading data based on digital family content under distributed storage |
| CN103853613A (en) * | 2012-12-04 | 2014-06-11 | 中山大学深圳研究院 | Method for reading data based on digital family content under distributed storage |
| CN104516945A (en) * | 2014-11-18 | 2015-04-15 | 国家电网公司 | Hadoop distributed file system metadata storage method based on relational data base |
| CN105007172A (en) * | 2015-05-28 | 2015-10-28 | 杭州健港信息科技有限公司 | Method for realizing HDFS high-availability scheme |
| CN105701178A (en) * | 2016-01-05 | 2016-06-22 | 北京汇商融通信息技术有限公司 | Distributed image storage system |
| CN106156359A (en) * | 2016-07-28 | 2016-11-23 | 四川新环佳科技发展有限公司 | A kind of data synchronization updating method under cloud computing platform |
| CN107911474A (en) * | 2017-12-04 | 2018-04-13 | 神州租屏(厦门)网络技术有限公司 | A kind of screen management system based on Internet of Things |
| CN111694791A (en) * | 2020-04-01 | 2020-09-22 | 新华三大数据技术有限公司 | Data access method and device in distributed basic framework |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102130950A (en) * | 2011-03-14 | 2011-07-20 | 中国科学技术大学苏州研究院 | Distributed monitoring system based on Hadoop cluster and monitoring method thereof |
| CN102255926A (en) * | 2010-05-17 | 2011-11-23 | 中国移动通信集团公司 | Task distribution method in map reduce (MR) system, system and apparatus thereof |
-
2012
- 2012-02-28 CN CN201210048934.3A patent/CN102638566B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102255926A (en) * | 2010-05-17 | 2011-11-23 | 中国移动通信集团公司 | Task distribution method in map reduce (MR) system, system and apparatus thereof |
| CN102130950A (en) * | 2011-03-14 | 2011-07-20 | 中国科学技术大学苏州研究院 | Distributed monitoring system based on Hadoop cluster and monitoring method thereof |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102882927B (en) * | 2012-08-29 | 2016-12-21 | 华南理工大学 | A kind of cloud storage data syn-chronization framework and its implementation |
| CN102882927A (en) * | 2012-08-29 | 2013-01-16 | 华南理工大学 | Cloud storage data synchronizing framework and implementing method thereof |
| CN102880531A (en) * | 2012-09-27 | 2013-01-16 | 新浪网技术(中国)有限公司 | Database backup system and backup method and slave database server of database backup system |
| CN103023995A (en) * | 2012-11-29 | 2013-04-03 | 中国电力科学研究院 | Hadoop-based distributive type cloud storage type automatic grading data managing system |
| CN103023995B (en) * | 2012-11-29 | 2015-09-09 | 中国电力科学研究院 | A kind of distributed cloud based on Hadoop stores automatic classification data management system |
| CN103853612A (en) * | 2012-12-04 | 2014-06-11 | 中山大学深圳研究院 | Method for reading data based on digital family content under distributed storage |
| CN103853613A (en) * | 2012-12-04 | 2014-06-11 | 中山大学深圳研究院 | Method for reading data based on digital family content under distributed storage |
| CN103024020A (en) * | 2012-12-05 | 2013-04-03 | 蓝盾信息安全技术股份有限公司 | Network data file storing method and device based on WEB application |
| CN103024020B (en) * | 2012-12-05 | 2015-06-03 | 蓝盾信息安全技术股份有限公司 | Network data file storing method and device based on WEB application |
| CN103124299A (en) * | 2013-03-21 | 2013-05-29 | 杭州电子科技大学 | Distributed block-level storage system in heterogeneous environment |
| CN103428292A (en) * | 2013-08-20 | 2013-12-04 | 浪潮集团有限公司 | Device and method for effectively storing big data |
| CN104516945A (en) * | 2014-11-18 | 2015-04-15 | 国家电网公司 | Hadoop distributed file system metadata storage method based on relational data base |
| CN105007172A (en) * | 2015-05-28 | 2015-10-28 | 杭州健港信息科技有限公司 | Method for realizing HDFS high-availability scheme |
| CN105701178A (en) * | 2016-01-05 | 2016-06-22 | 北京汇商融通信息技术有限公司 | Distributed image storage system |
| CN105701178B (en) * | 2016-01-05 | 2017-06-09 | 北京汇商融通信息技术有限公司 | Distributed picture storage system |
| CN106156359A (en) * | 2016-07-28 | 2016-11-23 | 四川新环佳科技发展有限公司 | A kind of data synchronization updating method under cloud computing platform |
| CN106156359B (en) * | 2016-07-28 | 2019-05-21 | 广东奥飞数据科技股份有限公司 | A kind of data synchronization updating method under cloud computing platform |
| CN107911474A (en) * | 2017-12-04 | 2018-04-13 | 神州租屏(厦门)网络技术有限公司 | A kind of screen management system based on Internet of Things |
| CN111694791A (en) * | 2020-04-01 | 2020-09-22 | 新华三大数据技术有限公司 | Data access method and device in distributed basic framework |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102638566B (en) | 2015-03-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102638566B (en) | BLOG system running method based on cloud storage | |
| CN110809017B (en) | Data analysis application platform system based on cloud platform and micro-service framework | |
| Zhang et al. | Research on key technologies of cloud computing | |
| CN102103518B (en) | System for managing resources in virtual environment and implementation method thereof | |
| CN105843182A (en) | Power dispatching accident handling scheme preparing system and power dispatching accident handling scheme preparing method based on OMS | |
| CN111274001B (en) | Micro-service management platform | |
| WO2016101638A1 (en) | Operation management method for electric power system cloud simulation platform | |
| CN107329799A (en) | A kind of fusion Docker containers and the system of KVM virtualization technology | |
| Lu et al. | Cloud computing survey | |
| CN102681899A (en) | Virtual computing resource dynamic management system of cloud computing service platform | |
| CN102594919B (en) | Information technology (IT) resource supporting system | |
| CN103699425A (en) | Software T/C/V architecture based on cloud computing and cloud computing method thereof | |
| CN105681474A (en) | System architecture for supporting upper layer applications based on enterprise-level big data platform | |
| CN112099917B (en) | Regulation and control system containerized application operation management method, system, equipment and medium | |
| CN114691050B (en) | Cloud native storage method, device, equipment and medium based on kubernets | |
| CN103685572A (en) | Method and system for building data center management platform based on SOA (service-oriented architecture) | |
| CN104536805A (en) | Resource providing system and method of virtualization platform | |
| Perri et al. | Implementing a scalable and elastic computing environment based on cloud containers | |
| CN103458050A (en) | Electronic reading room set-up method based on cloud computation | |
| CN107528871A (en) | Data analysis in storage system | |
| CN112667360A (en) | Cloud platform system based on Kubernetes and docker unified scheduling | |
| Yu et al. | Design and implementation of business access control in new generation power grid dispatching and control system | |
| Pan et al. | An open sharing pattern design of massive power big data | |
| CN202652266U (en) | Enterprise cloud computing common information service platform core architecture and system application | |
| Ma | Research and implementation of distributed storage system based on big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20150304 Termination date: 20170228 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |